Gene-environment interaction is a seminal concept in the molecular epidemiology of human cancer. Our case-control (using hospital- and population-based controls) studies focus on lung cancer, a tobacco-related cancer, and colon cancer, one of the cancer types associated with chronic inflammation. These studies require the integration of an increasing understanding of genetic variation in cancer susceptibility, analysis of carcinogen exposure, rapidly developing technologies, bioinformatics, social-ethical concerns, and epidemiological study-design methods. We discovered that common genetic variation in TP53 is associated with lung cancer risk and prognosis in African Americans and somatic mutations in lung tumors. We have developed a novel bioinformatic approach to identify SNP-SNP interactions and generate hypotheses. In collaboration with Alavanja, we have extended our previous molecular epidemiological studies of lung cancer in never-smoking women. In addition to the GSTM1-null polymorphism increasing the risk of secondhand smoke-induced lung cancer, GSTM1 null also increases the risk of environmental radon-induced lung cancer in these women. We are continuing our longstanding studies of human lung carcinogenesis. The molecular profile of adenocarcinoma identified smoking- versus nonsmoking-associated cancers and short-term versus long-term survivors. We have also discovered molecular profiles of inflammatory cytokines or microRNAs, nonprotein coding genes that identify lung cancer, its different histological types and prognosis. These findings are being extended to other cancer types including colon and esophageal cancer, and to animal models of human cancer.